Effect of the angiotensin-receptor-neprilysin inhibitor LCZ696 compared with enalapril on mode of death in heart failure patients
Bibliographic record
Abstract
AIMS: The angiotensin-receptor-neprilysin inhibitor (ARNI) LCZ696 reduced cardiovascular deaths and all-cause mortality compared with enalapril in patients with chronic heart failure in the prospective comparison of ARNI with an Angiotensin-Converting Enzyme Inhibitor to Determine Impact on Global Mortality and Morbidity in Heart Failure (PARADIGM-HF) trial. To more completely understand the components of this mortality benefit, we examined the effect of LCZ696 on mode of death. METHODS AND RESULTS: PARADIGM-HF was a prospective, double-blind, randomized trial in 8399 patients with chronic heart failure, New York Heart Association Class II-IV symptoms, and left ventricular ejection fraction ≤40% receiving guideline-recommended medical therapy and followed for a median of 27 months. Mode of death was adjudicated by a blinded clinical endpoints committee. The majority of deaths were cardiovascular (80.9%), and the risk of cardiovascular death was significantly reduced by treatment with LCZ (hazard ratio, HR 0.80, 95% CI 0.72-0.89, P < 0.001). Among cardiovascular deaths, both sudden cardiac death (HR 0.80, 95% CI 0.68-0.94, P = 0.008) and death due to worsening heart failure (HR 0.79, 95% CI 0.64-0.98, P = 0.034) were reduced by treatment with LCZ696 compared with enalapril. Deaths attributed to other cardiovascular causes, including myocardial infarction and stroke, were infrequent and distributed evenly between treatment groups, as were non-cardiovascular deaths. CONCLUSIONS: LCZ696 was superior to enalapril in reducing both sudden cardiac deaths and deaths from worsening heart failure, which accounted for the majority of cardiovascular deaths. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/, NCT01035255.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".